def OnSelectModel(self, evt):
dlg = wx.FileDialog(self, "Selectionnez le modele", os.path.join(os.getcwd(),MODEL_FOLDER), DEFAULT_MODEL_FILE,
wildcard = "Model files (*.svm)|*.svm",
style = wx.OPEN)
retour = dlg.ShowModal()
self.chemin = dlg.GetPath().encode("latin-1")
fichier = dlg.GetFilename().encode("latin-1")
dlg.Destroy()
if retour == wx.ID_OK and fichier != "":
self.model = Break_Captcha_util.load_model(self.chemin, self, fichier)
self.Update()
def OnSelectModel(self, evt):
dlg = wx.FileDialog(self, "Selectionnez le modele", os.path.join(os.getcwd(),MODEL_FOLDER), DEFAULT_MODEL_FILE,
wildcard = "Model files (*.svm)|*.svm",
style = wx.OPEN)
retour = dlg.ShowModal()
self.chemin = dlg.GetPath().encode("latin-1")
fichier = dlg.GetFilename().encode("latin-1")
dlg.Destroy()
if retour == wx.ID_OK and fichier != "":
self.model = Break_Captcha_util.load_model(self.chemin, self, fichier)
self.Update()
def OnSelectCaptcha(self, evt):
dlg = wx.FileDialog(self, "Selectionnez l'image", os.path.join(os.getcwd(), CAPTCHA_FOLDER), DEFAULT_CAPTCHA_FILE,
wildcard = "Image files (*.jpg;)|*.jpg",
style = wx.OPEN)
retour = dlg.ShowModal()
self.chemin = dlg.GetPath().encode("latin-1")
fichier = dlg.GetFilename()
dlg.Destroy()
if retour == wx.ID_OK and fichier != "":
self.captcha, self.beau_captcha = Break_Captcha_util.preprocess_captcha_part(self.chemin, self)
self.setCaptchaImage(self.beau_captcha)
self.captcha_selected = True
self.Update()
def OnSelectCaptcha(self, evt):
dlg = wx.FileDialog(self, "Selectionnez l'image", os.path.join(os.getcwd(), CAPTCHA_FOLDER), DEFAULT_CAPTCHA_FILE,
wildcard = "Image files (*.jpg;)|*.jpg",
style = wx.OPEN)
retour = dlg.ShowModal()
self.chemin = dlg.GetPath().encode("latin-1")
fichier = dlg.GetFilename()
dlg.Destroy()
if retour == wx.ID_OK and fichier != "":
self.captcha, self.beau_captcha = Break_Captcha_util.preprocess_captcha_part(self.chemin, self)
self.setCaptchaImage(self.beau_captcha)
self.captcha_selected = True
self.Update()
def compute_scores_list(model, captcha, parent=None):
#Liste des scores
liste_scores = []
#Compute scores for all widths and starting positions
for size in range(8, 30, 1):
print size, "/", 30
for starting_pos in range(0, captcha.size[0] - size):
preprocessed_captcha_part = captcha.crop(
(starting_pos, 0, starting_pos + size, 31))
#Si parent=None, on enlève le blanc sur les cotés
miny = 100000
maxy = 0
for i in xrange(size):
for j in xrange(31):
if preprocessed_captcha_part.getpixel((i, j)) == 0:
if j < miny:
miny = j
if j > maxy:
maxy = j
preprocessed_captcha_part = preprocessed_captcha_part.crop(
(0, miny, size, maxy + 1))
sizei = maxy - miny + 1
im = Image.new('L', (31, 31), 1)
im.paste(preprocessed_captcha_part,
((31 - size) / 2, (31 - sizei) / 2))
prediction, max_score = Break_Captcha_util.predict(
model, im, None, 0)
#liste_scores.append((starting_pos+size, size, 1/(1-max_score), prediction))
liste_scores.append(
(starting_pos + size, size, math.log(max_score), prediction))
if not parent:
f = open('scores.pck', 'w')
pickle.dump(liste_scores, f)
f.close()
return liste_scores
def compute_scores_list(model, captcha, parent=None):
#Liste des scores
liste_scores = []
#Compute scores for all widths and starting positions
for size in range(8, 30, 1):
print size, "/", 30
for starting_pos in range(0, captcha.size[0] - size):
preprocessed_captcha_part = captcha.crop((starting_pos, 0, starting_pos+size, 31))
#Si parent=None, on enlève le blanc sur les cotés
miny=100000
maxy=0
for i in xrange(size):
for j in xrange(31):
if preprocessed_captcha_part.getpixel((i,j)) == 0:
if j<miny:
miny=j
if j>maxy:
maxy=j
preprocessed_captcha_part = preprocessed_captcha_part.crop((0, miny, size, maxy+1))
sizei = maxy-miny+1
im = Image.new('L', (31, 31), 1)
im.paste(preprocessed_captcha_part, ((31-size)/2, (31-sizei)/2))
prediction, max_score = Break_Captcha_util.predict(model, im, None, 0)
#liste_scores.append((starting_pos+size, size, 1/(1-max_score), prediction))
liste_scores.append((starting_pos+size, size, math.log(max_score), prediction))
if not parent:
f=open('scores.pck', 'w')
pickle.dump(liste_scores, f)
f.close()
return liste_scores
for y in xrange(0, h):
segmented_captcha.putpixel((x*parent.zoom, y), (255,0,0))
parent.SetGraphImage(segmented_captcha)
parent.actif = False
parent.launchPredictionButton.SetLabel("Lancer la prédiction")
if __name__ == "__main__":
MODEL_FILE = "Hotmail/Models/model_31x31_3DE2MT_DXDY.svm"
#MODEL_FILE = "Hotmail/Models/model_31x31_3DE2MT_classes.svm"
CAPTCHA_FILE = os.path.join("Hotmail", "Rough Captchas", 'Image011.jpg')
#Chargement du modèle
model = Break_Captcha_util.load_model(MODEL_FILE)
#Préprocessing du captcha
captcha, beau_captcha = Break_Captcha_util.preprocess_captcha_part(CAPTCHA_FILE)
#Calcul des scores
liste_scores = compute_scores_list(model, captcha)
#Chargement des scores sauvegardés
## f=open('scores.pck')
## liste_scores = pickle.load(f)
## f.close()
use_dynamic_programming(liste_scores)
raw_input()
for x in segs:
for y in xrange(0, h):
segmented_captcha.putpixel((x * parent.zoom, y), (255, 0, 0))
parent.SetGraphImage(segmented_captcha)
parent.actif = False
parent.launchPredictionButton.SetLabel("Lancer la prédiction")
if __name__ == "__main__":
MODEL_FILE = "Hotmail/Models/model_31x31_3DE2MT_DXDY.svm"
#MODEL_FILE = "Hotmail/Models/model_31x31_3DE2MT_classes.svm"
CAPTCHA_FILE = os.path.join("Hotmail", "Rough Captchas", 'Image011.jpg')
#Chargement du modèle
model = Break_Captcha_util.load_model(MODEL_FILE)
#Préprocessing du captcha
captcha, beau_captcha = Break_Captcha_util.preprocess_captcha_part(
CAPTCHA_FILE)
#Calcul des scores
liste_scores = compute_scores_list(model, captcha)
#Chargement des scores sauvegardés
## f=open('scores.pck')
## liste_scores = pickle.load(f)
## f.close()
use_dynamic_programming(liste_scores)
raw_input()